Mathematical Modeling workshops

This workshop connects mathematical and theoretical neuroscience approaches to the dynamics of densely connected recurrent spiking networks. Mean-field methods link individual-neuron dynamics with population behaviour, while low-dimensional collective dynamics and low-rank connectivity provide complementary descriptions informed by experiments and simulations. Researchers with mathematical and physics backgrounds alternate presentations to compare these perspectives. Public research lectures run from Monday afternoon through Wednesday, followed by doctoral tutorials on Thursday and Friday at the Bernoulli Center, EPFL, Lausanne. Registration begins at 13:30 on 2 November, with the introduction at 13:45 and talks from 14:00. Tuesday and Wednesday lectures and Thursday and Friday tutorials start at 09:00. Times are Europe/Zurich, CET (UTC+01:00). Seats are limited; researchers from outside EPFL pay CHF90 and commit to attending the lecture sessions. Tutorials are restricted to PhD students. Separate registration forms for doctoral students and other researchers are linked on the official workshop page. Preparation assumes mathematics or physics at master’s level and familiarity with computational neuroscience.

The second M4H workshop brings mathematics, data science and medical research together to improve care. Mathematical models, numerical methods, statistics and machine learning support precision medicine, healthcare-resource allocation and multimodal patient-data analysis. Keynotes examine evolutionary cancer treatment and model-driven digital twins, longitudinal health records, topology and geometry for cyclic gene expression, statistical approaches to individual mental-health variation and patient-specific blood-flow simulation. Panels connect these methods with cardiovascular medicine, health data science and sustainable brain health. The Department of Mathematics at Politecnico di Milano hosts the in-person workshop on 11–13 November 2026 in Aula Rogers, Building 11, Via Ampère 2, Milan. Posters use Aula Vetrata, Trifoglio Building 13, Via Bonardi 9. The programme runs 11 November 14:00–19:30, 12 November 09:00–18:10 and 13 November 09:00–16:00. Times are Europe/Rome, CET (UTC+01:00). Registration is free and open until 15 October through the form on the official workshop page. Speaking slots are invitation only; general attendance is open, and participants may submit poster abstracts.

Genomics, proteomics and imaging now measure molecules and cells across many scales. This workshop examines how mechanistic models can integrate those measurements and biological dynamics to explain and engineer cellular behaviour. Researchers in single-cell analysis, dynamic proteomics, quantitative imaging, synthetic biology and theory will connect experimental and computational approaches. The programme links three themes: cell dynamics and interactions; molecular mechanisms and engineering; and rigorous quantitative models. Sessions address multiscale modelling, molecules over time, large-scale perturbations, prediction of cell states, dynamic processes, and stem-cell engineering. Virtual participation includes livestreamed talks, questions and discussion, plus available recordings for four weeks; individual speakers may decline recording. Virtual participants cannot submit presentation abstracts. Fees: PhD students €175, academia €200, industry €275; card payment is required. Virtual registration closes 10 November 2026. On-site registration is closed. Programme times are Europe/Berlin (CET, UTC+1): 17 November opening at 13:15 and talks from 13:30; 18 and 19 November sessions from 09:00; 20 November from 10:00, with closing remarks at 13:15–13:30.

This four-day workshop combines whole-brain modelling, machine learning and high-order interaction analysis to study human neuroimaging data beyond pairwise descriptions. Through reproducible Python workflows, participants combine theory-driven simulations with multivariate descriptors of collective brain dynamics to capture individual variability, explore brain health and support more mechanistic analyses of M/EEG and fMRI data. Opening lectures by Rodrigo Cofré on whole-brain models and high-order interactions, Kaichao Wu on modelling brain criticality in health and disease, Yonatan Sanz Perl on brain modelling and the physics of cognition, and Joana Cabral on functional connectivity as eigenmode resonance are followed by theory and hands-on tutorials on brain clocks (Carlos Coronel), brain high-order interactions (Marilyn Gatica), propagation of perturbations in brain networks (Xiaoge Bao) and HOI-based digital twins (Rubén Herzog), with poster sessions and flash talks. Lei Zhao gives the closing lecture on cognitive impairments in chronic pain within a brain-ageing framework, and the final day is devoted to developing project proposals in collaborative groups. Sessions run from 10:00 to 18:30 on 17–20 November 2026 at the Complex Balear de Recerca, Parc BIT, Universitat de les Illes Balears, in Palma de Mallorca. The workshop is held in person and in English for 40 participants selected by application, with no registration fee, and targets students and early-career researchers with scientific Python experience; applications closed on 25 September 2026.

Connect numerical approaches to classical and quantum initial-boundary-value problems. The workshop examines deterministic wave propagation, fluid dynamics and general relativity alongside fluctuating quantum fields and hydrodynamics. Invited perspectives and contributed talks explore shared modelling challenges, including symmetry-preserving and mimetic discretisation, summation-by-parts methods, action-based formulations, lattice field theory, stochastic partial differential equations and quantum computing. Researchers in theoretical physics and applied mathematics will compare methods and identify opportunities for collaboration across these neighbouring fields. 19 November 2026 at 09:00 through 21 November at 17:00, Asia/Seoul (KST, UTC+9). Participant registration closes on 8 November 2026 and requires an Indico account. Capacity is 70. Contributed abstracts are due 25 October.

CIFMA connects researchers studying cognition across psychology, neuroscience, linguistics, philosophy, education, robotics and computer science. The workshop explores attention, memory, reasoning, language, learning and human interaction with physical and computational environments. It brings formal modelling and analysis methods into dialogue with cognitive science, with applications in cognitive robotics, biomedical signals and imaging, neural interfaces, human–computer interaction and intelligent educational systems. The meeting is co-located with SEFM 2026 in Malta. Abstract and paper submission deadlines have passed.

The second UK Theoretical Neuroscience Workshop is a one-day meeting of talks and posters on mathematical and computational approaches to brain function, organised by Stephen Coombes (University of Nottingham) and Dimitrios Pinotsis (City St George's, University of London). Talks include Peter Latham (UCL) on time and task management in complex environments; Magnus Richardson (University of Warwick) on spatiotemporal coarse-graining of activity within neurons and across networks; Rafal Bogacz (University of Oxford) on predictive dendrites as a foundation for biological learning; Arnd Roth (UCL) on brain-wide dendritic signals that exhibit circuit-specific behavioural modulation; Mark Humphries (University of Nottingham) on cortical control of rhythmic and discrete arm movements; Vladimir Litvak (UCL) on why the low effective dimensionality of the human functional connectome does not invalidate lesion network mapping; and Massimiliano Di Luca (University of Birmingham) on temporal inference in perception and coordinated action. Angus Chadwick (University of Edinburgh) and Eirini Mavritsaki (Birmingham City University) also speak. The workshop runs from 09:00 to 18:10 on Friday 18 December 2026 at City St George's, University of London, with talks in the Northampton Suite (B411) and posters in The Pavilion of the University Building, Northampton Square. Attendance is free but registration is mandatory. Poster abstracts are due on 20 November 2026, and a poster award will be given.

Mechanistic cancer models and data-driven learning offer complementary ways to understand tumour behaviour and improve individualized treatment. This workshop explores how mathematical modelling can be combined with machine and deep learning, bringing together data scientists and mathematical oncologists. Plenary lectures survey current developments, while collaborative group projects develop algorithms that integrate mechanistic knowledge with observations. The programme aims to turn methodological exchange into sustained collaborations and more informative approaches to personalized cancer care.

The seventh Latin-American Summer School in Computational Neuroscience (LACONEU) runs from 11 to 29 January 2027 at CIAE, Universidad de Valparaíso, in Valparaíso, Chile, bringing together students, researchers and experts from Latin America, North America and Europe. The school seeks to advance computational neuroscience in Latin America by combining mathematical and computational tools with applications in biomedical research and clinical practice. Its three modules cover neural models and artificial intelligence, reviewing approaches to modelling neural systems from single neurons and microcircuits to large-scale brain networks and behaviour; machine learning for the analysis of neural data, the simulation of brain processes and the intersection of AI and neuroscience; and diffusion MRI tractography, from the biophysical basis of diffusion MRI to preprocessing and fibre reconstruction for studying structural brain connectivity. Morning lectures by national and international faculty are complemented by hands-on tutorials, problem solving and data analysis, tutored research projects in the afternoons and evenings, and evening seminars open to all audiences. The school especially encourages applicants from Latin America, women and members of historically underrepresented groups in science.

This school and workshop joins physics, applied mathematics and ecology to understand ecological dynamics and biodiversity across scales. Students learn to connect empirical data with individual-based models, differential equations, stochastic dynamics and complex interaction networks. The curriculum addresses marine species fluctuations, metapopulations, microbial ecology, animal movement, spatial scaling of plant communities, habitat fragmentation and evolutionary rescue. The January 23–24 workshop includes invited and contributed talks, posters, and discussion of theoretical ecology's future in South America. Master's and doctoral students are the principal school audience; advanced undergraduates and postdoctoral researchers may also apply. There is no registration fee, and limited travel and local support is available. School applications closed on 25 October 2026; the workshop application deadline is 20 November 2026.

Build and evaluate short-term ecological forecasts by repeatedly linking observations, models and predictions. A biodiversity challenge uses shrub, rabbit and dung-beetle data from Doñana with remote-sensing measurements. Participants process time series and satellite indices, compare autoregressive, hierarchical, correlational and mechanistic models, propagate uncertainty and assess forecasts against benchmarks. Reproducible R workflows lead to a submitted forecast and discussion of how predictions support conservation and adaptive management. Live sessions: 25–29 January, 14:00–18:30 daily, Europe/Madrid (CET, UTC+01:00). Total 27.5 hours: 22.5 live plus five independent. English-language live online course; Fee €236 until 30 November, then €290; Ambassador rates €188.80/€232. VAT included. Capacity: 25. Basic R and an ecology or environmental-science background are required; forecasting experience is unnecessary. Registration requires acceptance; payment follows confirmation. Recordings are provided, but live attendance is required for a certificate.

Build and evaluate correlative species-distribution and ecological-niche models with R. The course connects niche theory with occurrence-data quality, environmental predictors, model fitting and validation, then examines spatial and temporal projections and their limitations. Participants learn to recognize common modelling pitfalls, automate reproducible analyses and apply workflows to example or personal species datasets. 2027-02-01–2027-02-05, 15:00–18:00 daily, Europe/Berlin (CET, UTC+01:00). Online course; fee €480. Basic R knowledge is strongly recommended. Live classes are complemented by about four hours of independent work daily and annotated scripts, with remote support available between 09:00 and 23:00 Berlin time.

Workshop bringing together researchers working on AI for learning dynamics from data, with a special focus on information-theoretic methods. Topics include predictive information, the information bottleneck, latent-variable models, entropy and mutual-information estimation, world models of biological systems, and connections to dynamical systems and control theory. The workshop is part of the six-week NITMB program “Image-Based Scientific Machine Learning for Theories of Biological Dynamics Across Scales” (February 1–March 12, 2027). Program: AI in Biological Dynamics Scientific Focus — details for the six-week NITMB program: https://www.nitmb.org/ai-in-biological-dynamics-scientific-focus Application deadlines: November 9, 2026 for applicants requesting travel and lodging support; December 8, 2026 for local applicants. Students, postdocs and early-career researchers are encouraged to apply. See the Application tab on the workshop website.

This course develops a species-distribution modelling workflow using Bayesian additive regression trees. Participants compare BART with other modelling approaches and use the R packages embarcadero and dbarts to choose environmental predictors, train and evaluate occurrence models, and predict presence or absence in new places or periods. The programme introduces Bayesian regression and boosted trees, then examines predictor effects, interactions, spatial effects and random-intercept BART models, with practical troubleshooting and interpretation. Live online teaching takes place from 15:00 to 18:00 Berlin time (CET, UTC+1) on 9–11 February 2027. The programme also specifies four additional hours of independent practical work using annotated R scripts and online support. Advanced students, researchers and practitioners should already know the basics of species-distribution modelling and be comfortable using RStudio, installing packages and editing simple scripts. A laptop, webcam and reliable internet connection are required. The standalone course fee is EUR 390.

Small-scale ocean mixing must be understood and represented accurately in climate models. This workshop joins mathematicians, numerical modellers, laboratory researchers, observational oceanographers and machine-learning specialists to connect mixing mechanisms with predictive parameterizations. Participants will compare theory, experiments and increasingly detailed observations, assess computational and learning approaches, and identify ways to transfer advances between disciplines. Early-career researchers will gain a broad view of the methods and collaborations needed to link mathematical descriptions to ocean behaviour.

GoEMMI (GOettingen EMergent Minds) is a three-week winter school on learning and computation in brains and machines, held from 15 February to 6 March 2027 at the Max Planck Institute for Dynamics and Self-Organization, Am Faßberg 17, Göttingen. The programme is organised around three blocks: the theory of emergence and computation, covering conceptual and mathematical frameworks for emergent macrovariables, dynamical autonomy, compositionality and information-theoretic approaches to computation and causality; learning in brains and machines, covering learning objectives, representation formation, neural world models, data-driven discovery of dynamical systems and connections between biological and artificial learning; and computation from local interactions, covering neural dynamics, synaptic plasticity, local learning rules and network mechanisms through which microscopic interactions support coherent computation at larger scales. Lectures and tutorials are complemented by a hackathon, lab tours, a poster session and a dedicated lecture on the philosophy and ethics of artificial intelligence. Speakers include Larissa Albantakis, Nicolas Brunel, Spyridon Chavlis, Adrienne Fairhall, Wulfram Gerstner, Anna Levina, Sarah Marzen, Francesca Mastrogiuseppe, Wiktor Młynarski, Vincent C. Müller, Gonzalo Polavieja, Fernando Rosas, Karoline Wiesner and David Wolpert, together with researchers from Göttingen. There are no registration fees; applications for the 20 student places were open until 1 October 2026.

Marking a century of Richardson’s work on turbulent dispersion, this programme compares Lagrangian and Eulerian approaches, stochastic and deterministic models, particle dynamics and continuum descriptions. Topics include multiparticle dispersion, experimental particle tracking, geophysical transport, spontaneous stochasticity, mixing, and machine-learning methods for closure and inference. The programme connects theory, simulation and experiment with environmental and climate prediction. It targets doctoral students, postdocs and established researchers in turbulence and transport; exceptional master’s students may be considered. Accommodation is provided for outstation participants.

Develop phylogenetic comparative methods from their probabilistic foundations using Julia. Participants implement likelihood and Bayesian inference, including Markov chain Monte Carlo, and study Brownian motion, continuous-time Markov chains and birth–death processes. These tools are applied to trait evolution, biogeography and diversification, including the effects of environmental and biotic interactions. The practical course is intended for researchers familiar with programming, probability and phylogenetics; prior Julia experience is not required. Sessions on 1, 3, 5, 8, 10 and 12 March 2027, 14:00–18:00 Madrid time (CET). Fee including VAT: EUR 492 through 31 December 2026, then EUR 576; Ambassador Institution rates EUR 393.60 and EUR 460.80. Limited to 18 participants. Acceptance is confirmed before payment. Delivered live online in English with practical exercises. Live attendance is required for a certificate.

A graduate school and research workshop examine water from molecular to planetary scales. The programme connects hydrogen bonding and quantum effects with collective dynamics, interfaces, biological function, extreme conditions and atmospheric water. Participants study first-principles simulations, machine-learned potentials and multiscale modelling. The first week provides foundational training; the second features current research, discussions and posters. Applicants should have grounding in statistical mechanics, quantum mechanics and molecular simulation or related computation. Graduate students, postdocs and early-career faculty are the main audience, with limited consideration of senior undergraduates. ICTS provides accommodation for outstation participants.

AI structure prediction and physics-based simulations provide complementary views of molecular interactions. This workshop integrates them to study conformational change, heterogeneity, disordered regions, molecular machines and multicomponent complexes. Around half of the programme comprises practical computational work, with participants using their own scientific problems in hands-on sessions, short presentations and troubleshooting discussions.